Deep Learning is Eating Software

When I had a drink with Andrej Karpathy a couple of weeks ago, we got to talking about where we thought machine learning was going over the next few years. Andrej threw out the phrase “Software 2.0”, and I was instantly jealous because it captured the process I see happening every day across hundreds of projects. I held my tongue until he got his blog post out there, but now I want to expand my thoughts on this too.

The pattern is that there’s an existing software project doing data processing using explicit programming logic, and the team charged with maintaining it find they can replace it with a deep-learning-based solution. I can only point to examples within Alphabet that we’ve made public, like upgrading search ranking, data center energy usage, language translation, and solving Go, but these aren’t rare exceptions…